Decentralized iterative learning control methods are presented for a class of large scale interconnected linear dynamic systems, in which an iterative learning controller in each subsystem operates on its local subsystem exclusively with no exchange of information between subsystems. Sufficient conditions for convergence of the algorithms are given and numerical examples are illustrated to show the validity of the algorithms. In particular, the algorithms are useful for systems having large uncertainty of interconnected terms.